愿望预测背后的认知机制:一个扩散模型分解
Jeremy D Strueder1, Inkyung Park1, J Toby Mordkoff1
1Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA.
Cognition
|December 4, 2025
概括
愿望思维,或可取性偏见,通过减少预期结果所需的证据来膨胀期望. 这种认知偏见也影响人们如何解释证据,证明了对动机推理的自上而下的影响.
科学领域:
- 认知心理学 认知心理学
- 决策科学 决策科学 决策科学
- 行为经济学是一种行为经济学.
背景情况:
- 愿望思维,或可取性偏见,发生在一个结果的愿望增加其发生的预期时.
- 以前的研究表明,结果的可取性会影响预测,但认知机制仍然不清楚.
- 潜在的机制包括有偏见的证据判断或有偏见的证据搜索和积累.
研究的目的:
- 使用漂移-扩散建模研究潜在的可取性偏见的认知机制.
- 确定在哪些处理级别的可取性对预测产生影响.
- 检查可取性如何影响证据判断和积累.
主要方法:
- 参与者 (N=147) 预测了从2色网格中随机选择的正方形的颜色.
- 结果的可取性被操纵,某些颜色比其他颜色更可取.
- 通过改变所需颜色方块的比例来改变证据的强度;采用漂移扩散建模.
主要成果:
- 无论是可取性操纵还是它们的相互作用都显著影响了预测.
- 漂移-扩散模型分析揭示了判断层面的偏见:预测所需结果所需的证据较少.
- 可取性影响了证据的积累,参与者更容易地解释证据支持所需结果 (自上而下的影响).
结论:
- 理想性偏差影响证据判断的门和证据积累的过程.
- 这表明欲望对预测相关信息的处理方式具有自上而下的影响.
- 漂移扩散建模是剖析有动机的认知偏见机制的一个有价值的工具.
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